Pallavi Jonnalagadda1, Christine Swoboda1, Priti Singh1, Harish Gureddygari1, Seth Scarborough1, Ian Dunn2, Nathan J Doogan2, Naleef Fareed1,3. 1. CATALYST, Center for the Advancement of Team Science, Analytics, and Systems Thinking in Health Services and Implementation Science Research, College of Medicine, The Ohio State University, Columbus, Ohio, United States. 2. The Ohio Colleges of Medicine Government Resource Center, Columbus, Ohio, United States. 3. Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio, United States.
Abstract
OBJECTIVES: Social determinants of health (SDoH) can be measured at the geographic level to convey information about neighborhood deprivation. The Ohio Children's Opportunity Index (OCOI) is a composite area-level opportunity index comprised of eight health domains. Our research team has documented the design, development, and use cases of a dashboard solution to visualize OCOI. METHODS: The OCOI is a multidomain index spanning the following eight domains: (1) family stability, (2) infant health, (3) children's health, (4) access, (5) education, (6) housing, (7) environment, and (8) criminal justice. Information on these eight domains is derived from the American Community Survey and other administrative datasets. Our team used the Tableau Desktop visualization software and applied a user-centered design approach to developing the two OCOI dashboards-main OCOI dashboard and OCOI-race dashboard. We also performed convergence analysis to visualize the census tracts where different health indicators simultaneously exist at their worst levels. RESULTS: The OCOI dashboard has multiple, interactive components as follows: a choropleth map of Ohio displaying OCOI scores for a specific census tract, graphs presenting OCOI or domain scores to compare relative positions for tracts, and a sortable table to visualize scores for specific county and census tracts. A case study using the two dashboards for convergence analysis revealed census tracts in neighborhoods with low infant health scores and a high proportion of minority population. CONCLUSION: The OCOI dashboards could assist health care leaders in making decisions that enhance health care delivery and policy decision-making regarding children's health particularly in areas where multiple health indicators exist at their worst levels. Thieme. All rights reserved.
OBJECTIVES: Social determinants of health (SDoH) can be measured at the geographic level to convey information about neighborhood deprivation. The Ohio Children's Opportunity Index (OCOI) is a composite area-level opportunity index comprised of eight health domains. Our research team has documented the design, development, and use cases of a dashboard solution to visualize OCOI. METHODS: The OCOI is a multidomain index spanning the following eight domains: (1) family stability, (2) infant health, (3) children's health, (4) access, (5) education, (6) housing, (7) environment, and (8) criminal justice. Information on these eight domains is derived from the American Community Survey and other administrative datasets. Our team used the Tableau Desktop visualization software and applied a user-centered design approach to developing the two OCOI dashboards-main OCOI dashboard and OCOI-race dashboard. We also performed convergence analysis to visualize the census tracts where different health indicators simultaneously exist at their worst levels. RESULTS: The OCOI dashboard has multiple, interactive components as follows: a choropleth map of Ohio displaying OCOI scores for a specific census tract, graphs presenting OCOI or domain scores to compare relative positions for tracts, and a sortable table to visualize scores for specific county and census tracts. A case study using the two dashboards for convergence analysis revealed census tracts in neighborhoods with low infant health scores and a high proportion of minority population. CONCLUSION: The OCOI dashboards could assist health care leaders in making decisions that enhance health care delivery and policy decision-making regarding children's health particularly in areas where multiple health indicators exist at their worst levels. Thieme. All rights reserved.
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